Hi, I'm Lauren!
I design and build at the intersection of computer science and human experience. My work spans conversational AI agent development, game AI research, and immersive design. Always exploring what technology can do when it actually talks back.
About Me
Lauren is a professionally trained dancer and software developer with a passion for building AI systems that connect with people. Initially moving to NYC to pursue dance, she pivoted to a BS then MS in Computer Science, where she found that her background in performance gave her a unique lens for designing technology that feels intuitive and human.
She works across AI agent development, machine learning research, and immersive design. She loves building systems that range from conversational voice agents and adaptive learning tools to reinforcement learning experiments and game AI. She also founded the Google Developer Group at Pace University, where she coordinated the coordination of 10+ workshops on AI, Gemini CLI, and Google Cloud, connecting students with NYC's broader tech community.
Outside of her work, she enjoys exploring new coffee shops, traveling, and attending theater.
My Skills
Collection of technologies and tools that I am skilled in using and developing with.
Portfolio
Here are some of my favorite research, community, and game development projects that I have gotten the opportunity to create.
ORRUS by Team Oculus
Growing investment in space and affordable satellites have significantly increased launches over the past decade, risking a future where space is choked with defunct satellites and debris. To address this and promote sustainable use, we advocate for the International Coalition of Space Programs, uniting global stakeholders. Its cornerstone, ORRUS, will actively collect and track space debris, preserving our orbital environment.
GDG on Campus at Pace University
Founder of GDG on Campus at Pace University, organizing 10+ AI-focused workshops on chatbot development, Gemini CLI, and Google Cloud. Partnered with GDG NYC and GDG Brooklyn to connect Pace students with NYC's broader AI/ML professional community.
Adaptability of Reinforcement Learning Agent from Simple to Complex Environments
Reinforcement learning agents trained with raycast sensors outperformed those with visual input in navigating complex environments after simple environment training, with added benefits of smaller models and faster training.
Ruckus at Revolver Ridge
VR game made for Meta Quest 2 using Unity. Developed by Lauren DeMaio and Andrew Dinspechin.
Escape
Can you escape? Collect the jewels and avoid the fire or you will have to start from the beginning! Developed by Lauren DeMaio.
Bide && Sneak
Bide && Sneak is a 2nd-Person slasher - see only from the perspective of your enemies, but never yourself. Use their viewpoints to figure out your position, then vanish and strike from the shadows. The last man standing is NOT the winner. Cowardice will not be rewarded. Developed by Lauren DeMaio and Andrew Dinspechin.
ASMO
Game developed for BIP Game Jam with HdM in Stuttgart, Germany. The theme for the game jam was Fighting Misinformation. Our game ASMO is a conglomerate of misinformation as you enter the world as an alien who works his way up to President to tell his citizens their water is radioactive. Developed by Lauren, Fabian, Jesse, and Lauri.
Evaluating Observations vs. Training Duration in Reinforcement Learning
Reinforcement learning is a reward-based method where an AI agent learns by taking actions based on environmental observations. The agent receives positive or negative rewards for its actions towards a goal. This project evaluated how different levels of observations affect training time by comparing them to the episodes needed for an agent to achieve its goal consistently.
Yoga Pose Estimation Using BlazePose and Machine Learning
Yoga is a popular mind-body practice with many health benefits. This project uses BlazePose and machine learning to detect yoga poses, utilizing a dataset of seven different asanas. This application is particularly relevant for online physical education, given the growth of self-paced online courses.
Publications
My published research and academic papers.
The Nintendo Artificial Neural Network System
Dr. Carmine Guida, Lauren DeMaio - Pace University Seidenberg School of CSIS, 2025
Artificial Neural Networks (ANN) are used in a variety of machine learning tasks such as image classification and pattern recognition. Training ANN models on large datasets can be time consuming and require specialized hardware and processing power. Often, the training is performed on powerful systems, and the resultant final trained network can be utilized on small computers and mobile devices to perform tasks instantly. The Nintendo Entertainment System (NES) was released in 1985 and featured a 1.79 MHz CPU and 2 KB of RAM. The original program code for games for the NES fit within 32 KB of ROM on cartridges. In this work, we create an ANN and train it using the EMNIST hand-drawn digit dataset on a desktop computer. This ANN is then ported to the NES utilizing assembly language. The program code and pretrained weights are stored to a game cartridge fitting within the bounds of 32 KB. Additionally, a user interface is provided for drawing and loading test samples and executing the ANN classification of hand drawn digits on a physical NES device from 40 years ago.
Read PaperMedia Features
Dancing Through Algorithms: Transitioning from Dance to Tech
Lauren DeMaio (BS in Computer Science 2024) is a senior at the Seidenberg School, who mixes the art of dance with the science of computing. Join us as we walk through Laurens typical day on campus, her lattes, her algorithms, and the story of how her decisions have led to an adventure in learning and teaching, at Pace.
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Leveling Up: Pace Students Join International Game Jam
Students from Pace University’s Seidenberg School of Computer Science and Information Systems concluded the Spring 2025 semester with an international trip—by teaming up with peers from across Europe to take on disinformation through game design.
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Celebrating Innovation: highlights from the ATTRACT Pre-Final Conference
Lauren DeMaio got to present the project ORRUS by Team Oculus at the ATTRACT PreFinal Conference in Grenoble, France. Here she is featured in a video describing the impact of the ATTRACT Student Programs.
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Pace Students Attend Games for Change Festival
Finding ways to power up the impact of gaming on wellbeing has enduring appeal, so when a group of gaming and computer science students attended the Games for Change Festival, held at The New School in NYC, there was plenty to get excited about.
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Seidenberg’s Impact at Google’s DevFest: Responsible AI Takes Center Stage
Seidenbergs Lauren DeMaio, an MS in Computer Science student and leader of the Google Developer Student Club at Pace, introduced two of the events speakers, further showing her dedication to bridging academic learning with industry practice.
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New Club Alert: Pace’s Seidenberg School Launches Google Developer Student Club
Pace University’s Seidenberg School of Computer Science and Information Systems recently launched a Google Developer Student Club (GDG) on the New York City campus. The Google Developer Student Club at Pace is led by Seidenberg graduate student Lauren DeMaio and mentored by Seidenberg Professor, Associate Dean, and Co-Director of the Pace AI Lab, Dr. Christelle Scharff.
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Nespresso Retail Hiring Event Video
Lauren was asked what her favorite part of working at Nespresso is as a Team Leader.
Read MoreLet's Chat!
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